Annotation of SBML Models Through Rule-Based Semantic Integration

*Motivation:* The creation of accurate quantitative Systems Biology Markup Language (SBML) models is a time-intensive, manual process often complicated by the many data sources and formats required to annotate even a small and well-scoped model. Ideally, the retrieval and integration of biological knowledge for model annotation should be performed quickly, precisely, and with a minimum of manual effort. Here, we present a method using off-the-shelf semantic web technology which enables this process: the heterogeneous data sources are first syntactically converted into ontologies; these are then aligned to a small domain ontology by applying a rule base. Integrating resources in this way can accommodate multiple formats with different semantics; it provides richly modelled biological knowledge suitable for annotation of SBML models.
*Results:* We demonstrate proof-of-principle for this rule-based mediation with two use cases for SBML model annotation. This was implemented with existing tools, decreasing development time and increasing reusability. This initial work establishes the feasibility of this approach as part of an automated SBML model annotation system.
*Availability:* Detailed information including download and mapping of the ontologies as well as integration results is available from "http://www.cisban.ac.uk/RBM":http://www.cisban.ac.uk/RB

Heterogeneity in pure microbial systems: experimental measurements and modeling

Cellular heterogeneity influences bioprocess performance in ways that until date are not completely elucidated. In order to account for this phenomenon in the design and operation of bioprocesses, reliable analytical and mathematical descriptions are required. We present an overview of the single cell analysis, and the mathematical modeling frameworks that have potential to be used in bioprocess control and optimization, in particular for microbial processes. In order to be suitable for bioprocess monitoring, experimental methods need to be high throughput and to require relatively short processing time. One such method used successfully under dynamic conditions is flow cytometry. Population balance and individual based models are suitable modeling options, the latter one having in particular a good potential to integrate the various data collected through experimentation. This will be highly beneficial for appropriate process design and scale up as a more rigorous approach may prevent a priori unwanted performance losses. It will also help progressing synthetic biology applications to industrial scale

BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology

BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism

Recombinant Protein Production with Escherichia coli in Glucose and Glycerol Limited Chemostats

Recently, there has been a resurgence of interest in continuous bioprocessing as a cost-optimised production strategy, driven by a rising global requirement for recombinant proteins used as biological drugs. This strategy could provide several benefits over traditional batch processing, including smaller bioreactors, smaller facilities, and overall reduced plant footprints and investment costs. Continuous processes may also offer improved product quality and minimise heterogeneity, both in the culture and in the product. In this paper, a model protein, green fluorescent protein (GFP) mut3*, was used to test the recombinant protein expression in an Escherichia coli strain with industrial relevance grown in chemostat. An important factor in enabling stable productivity in continuous cultures is the carbon source. We have studied the viability and heterogeneity of the chemostat cultures using a chemically defined medium based on glucose or glycerol as the single carbon source. As a by-product of biodiesel production, glycerol is expected to become a sustainable alternative substrate to glucose. We have found that although glycerol gives a higher cell density, it also generates higher heterogeneity in the culture and a less stable recombinant protein production. We suggest that manipulating the balance between different subpopulations to increase the proportion of productive cells may be a possible solution for making glycerol a successful alternative to glucose

A Novel Extracellular Metallopeptidase Domain Shared by Animal Host-Associated Mutualistic and Pathogenic Microbes

The mucosal microbiota is recognised as an important factor for our health, with many disease states linked to imbalances in the normal community structure. Hence, there is considerable interest in identifying the molecular basis of human-microbe interactions. In this work we investigated the capacity of microbes to thrive on mucosal surfaces, either as mutualists, commensals or pathogens, using comparative genomics to identify co-occurring molecular traits. We identified a novel domain we named M60-like/PF13402 (new Pfam entry PF13402), which was detected mainly among proteins from animal host mucosa-associated prokaryotic and eukaryotic microbes ranging from mutualists to pathogens. Lateral gene transfers between distantly related microbes explained their shared M60-like/PF13402 domain. The novel domain is characterised by a zinc-metallopeptidase-like motif and is distantly related to known viral enhancin zinc-metallopeptidases. Signal peptides and/or cell surface anchoring features were detected in most microbial M60-like/PF13402 domain-containing proteins, indicating that these proteins target an extracellular substrate. A significant subset of these putative peptidases was further characterised by the presence of associated domains belonging to carbohydrate-binding module family 5/12, 32 and 51 and other glycan-binding domains, suggesting that these novel proteases are targeted to complex glycoproteins such as mucins. An in vitro mucinase assay demonstrated degradation of mammalian mucins by a recombinant form of an M60-like/PF13402-containing protein from the gut mutualist Bacteroides thetaiotaomicron. This study reveals that M60-like domains are peptidases targeting host glycoproteins. These peptidases likely play an important role in successful colonisation of both vertebrate mucosal surfaces and the invertebrate digestive tract by both mutualistic and pathogenic microbes. Moreover, 141 entries across various peptidase families described in the MEROPS database were also identified with carbohydrate-binding modules defining a new functional context for these glycan-binding domains and providing opportunities to engineer proteases targeting specific glycoproteins for both biomedical and industrial applications

More Than Meets the Kappa for Antibody Superantigen Protein L (PpL)

Immunoglobulin superantigens play an important role in affinity purification of antibodies and the microbiota-immune axis at mucosal areas. Based on current understanding, Staphylococcal Protein A (SpA), Streptococcal Protein G (SpG) and Finegoldia Protein L (PpL) are thought to only bind specific regions of human antibodies, allowing for selective purification of antibody isotypes and chains. Clinically, these superantigens are often classified as toxins and increase the virulence of the producing pathogen through unspecific interactions with immune proteins. To perform an in-depth interaction study of these three superantigens with antibodies, bio-layer interferometry (BLI) measurements of their interactions with a permutation panel of 63 IgG1 variants of Pertuzumab and Trastuzumab CDRs grafted to the six human Vκ and seven human VH region families were tested. Through this holistic and systemic analysis of IgG1 variants with various antibody regions modified, comparisons revealed novel PpL–antibody interactions influenced by other non-canonical antibody known light-chain framework regions, whereas SpA and SpG showed relatively consistent interactions. These findings have implications on PpL-based affinity antibody purification and design that can guide the engineering and understanding of PpL-based microbiota-immune effects

A genetic circuit compiler : generating combinatorial genetic circuits with web semantics and inference

A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in any of several languages or robotically assembled in vitro. In this paper we present a language, the Genetic Circuit Description Language (GCDL) and a compiler, the Genetic Circuit Compiler (GCC). This language describes genetic circuits at a level of granularity appropriate both for automated assembly in the laboratory and deriving simulation code. The GCDL follows Semantic Web practice, and the compiler makes novel use of the logical inference facilities that are therefore available. We present the GCDL and compiler structure as a study of a tool for generating ?-language simulations from semantic descriptions of genetic circuits

A Genetic Circuit Compiler: Generating Combinatorial Genetic Circuits with Web Semantics and Inference

A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in any of several languages or robotically assembled in vitro. In this paper we present a language, the Genetic Circuit Description Language (GCDL) and a compiler, the Genetic Circuit Compiler (GCC). This language describes genetic circuits at a level of granularity appropriate both for automated assembly in the laboratory and deriving simulation code. The GCDL follows Semantic Web practice and the compiler makes novel use of the logical inference facilities that are therefore available. We present the GCDL and compiler structure as a study of a tool for generating κ-language simulations from semantic descriptions of genetic circuits

Myco-Architecture off Planet: Growing Surface Structures at Destination

Our work focused on filling major select key technical knowledge gaps, and technical aspects to be addressed in a Phase II proposal were identified such as the secretion of glues or plastics by the fungi or bacteria to form biocomposites. Specifically, we raised the technical TRL by assessing the growth of in-house mycelial-producing strains on potential food substrates and analyzed the advantages and disadvantages to their use off planet. Growth of the mycelia on sawdust and powdered nutrients including dried, powdered algae, was used as a baseline. We measured growth as a function of temperature, tested the relevant material properties of the mycelia products produced, and measured the mass of input and output volume for production per volume of material. Mycotecture was produced in a bag simulating the proposed mission implementation. Post-production such as heat treatment (as is done with terrestrial mycotecture)was assessed.The material properties of the dried, frozen and baked mycelial outputs included density, strength,thermal insulation and flame retardation. Tensile/compression testing on biocomposite material specimens was performed to obtain three-dimensional elastic constants, as well as to examine deformation and fracture behavior. These mechanical tests were performed on both dormant and activated samples to understand the evolution of the structural material. In addition, experimental data obtained from the mechanical testing was used to build a failure prediction model that accounts for material anisotropy. This aided in future structural design through a quantitative understanding of the mechanical limits of the material. To examine the texture, defects, fracture surfaces of the material, high-resolution microstructural imaging was utilized before and after the mechanical tests. This microstructural analysis informed us about the macro-structural behavior and influenced structural design. Thermal decomposition analysis was also performed tounderstand the thermal limits